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A modified shape context method for shape based object retrieval

Overview of attention for article published in SpringerPlus, November 2014
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Mentioned by

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1 tweeter
facebook
1 Facebook page

Citations

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6 Dimensions

Readers on

mendeley
13 Mendeley
Title
A modified shape context method for shape based object retrieval
Published in
SpringerPlus, November 2014
DOI 10.1186/2193-1801-3-674
Pubmed ID
Authors

Radhika Mani Madireddy, Pardha Saradhi Varma Gottumukkala, Potukuchi Dakshina Murthy, Satyanarayana Chittipothula

Abstract

The complexity in shape context method and its simplification is addressed. A novel, but simple approach to design shape context method including Fourier Transform for the object recognition is described. Relevance of shape context, an important descriptor for the recognition process is detailed. Inclusion of information regarding all the contour points (with respect to a reference point) in computing the distribution is discussed. Role of similarity checking the procedure details regarding the computation of matching errors through the alignment transform are discussed. Present case of shape context (for each point with respect to the centroid) descriptor is testified for its invariance to translation, rotation and scaling operations. Euclidean distance is used during the similarity matching. Modified shape context based descriptor is experimented over three standard databases. The results evidence the relative efficiency of the modified shape context based descriptor than that reported for other descriptor of concurrent interests.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 8%
Unknown 12 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 46%
Student > Master 3 23%
Researcher 2 15%
Student > Postgraduate 1 8%
Unknown 1 8%
Readers by discipline Count As %
Computer Science 7 54%
Engineering 3 23%
Agricultural and Biological Sciences 1 8%
Environmental Science 1 8%
Unknown 1 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 November 2014.
All research outputs
#4,439,012
of 8,702,492 outputs
Outputs from SpringerPlus
#691
of 1,724 outputs
Outputs of similar age
#91,036
of 200,263 outputs
Outputs of similar age from SpringerPlus
#36
of 71 outputs
Altmetric has tracked 8,702,492 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,724 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 200,263 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.